Probabitlity - P(A orPP(AandB bjective P(B B P(A Variance...

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Objective P(A or B) = P(A) + P(B) P (A and B) = P(A)P(B|A) P (A and B) = P(A)P(B) P (A or B) = P(A) + P(B) – P (A or B) μ = [xP(x)] Mean and Variance = μ Probabitlity – measure of likelihood that an event will happen Experiment – process that leads to ONLY one of possible outcomes (toss coin) Outcome – a particular result of an experiment (HHT) Event – collection of one or more outcomes of an experiment (A= 2/3) Classical – based on outcomes that are equally likely (rolling a die) Empirical – approximate based on law of large numbers,history, relative frequency (more known= more accurate) Subjective – based on the little known information that you have (super bowl, married before age of 30) Mutually Exclusive – one event occurs, none of the other ones can occur at the same time Collectively Exhaustive – at least one of the events must occur (Politics is not) Independent – occurrence of one event does not affect the other Special Rule of Addition – events must be mutually exclusive General Rule of Addition when an event is NOT mutually exclusive Joint Probability - measures likelihood of two or more events happening at same time Special Rule of Multiplication – requires that A and B are independent General Rule – requires dependent (conditional probability - P (A|B)) Contingency Tables – table used to classify sample observations according to two or more identifiable characteristics (Individual/Ratio + Nominal/ordinal) % Increase/Decrease same Independent #/ total | #/# column Tree Diagram – helpful for several stages of unconditional (marginal), conditional and joint probabilities
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This note was uploaded on 11/04/2010 for the course SCM 200 taught by Professor Kumarsanjay during the Spring '08 term at Penn State.

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Probabitlity - P(A orPP(AandB bjective P(B B P(A Variance...

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